anderzzz / monkey_caput Goto Github PK

Hello，When I call the class 'AELearner' in the code in ae_runs. Py, I have the problem of 'the abstract class cannot be instantiated'.I have looked up a lot of information but failed to solve this problem, so I would like to ask if you have any good suggestions. I have not been in touch with this direction for a long time, and it is still difficult for me to reproduce the code, so I would like to ask you to send me a detailed introduction of the file order, or send me a code package that can run? It would be greatly appreciated if you could. If not, your reply will be greatly appreciated. My email address is [email protected].

Hi, I used ae_deep autoencoder to train it for my custom dataset i.e. plant dataset (contains plant leaves, weeds, and soil+ground). I then start it performed well. After the first epoch, it generated something that can be near original but a little fuzzy. So I continued the training but after the second epoch the result started getting bad and till the 10th epoch, it was all gray images.

Can you suggest to me the changes I can do that can be helpful to get a better-reconstructed image? I am using learning rate = 1e-3 and adam optimizer with weight decay =1e-5.

I have looked at the source code, and it seems that your image clustering is supervised. Where is autoencoder used, and how can I use autoencoder for unsupervised classification?

Hello, I want to reproduce the code in this paper, but I encountered a problem in the process, so I want to ask you for advice. I want to ask where are the files in the file path in "raw_csv_toc='../../Desktop/Fungi/toc_full.csv', raw_csv_root='../../Desktop/Fungi"In line 32 of ae_runs.py? Thank you for your time to look this and I look forward to your reply.

Great project! I was trying to reproduce the steps from your excellent tutorial, but noticed that the class for loading the fungi dataset is missing (e.g., from fungiimg import UnNormalizeTransform). Would it be possible to share the relevant code and data?

Hi,

I'd like to use this for unsupervised image clustering. Is it as simple as just swapping the example images with my own images, keeping the rest of the code the same? If so, how do I run this?